// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#pragma once

#include <fstream>
#include <paddle_ocr/preprocess_op.h>
#include <paddle_ocr/utility.h>
#include <iostream>
#include <memory>

namespace paddle_infer {
class Predictor;
}

namespace PaddleOCR {

class CRNNRecognizer {
public:
  /**
   * @brief 构造一个用于文本识别的 CRNNRecognizer 对象
   * 
   * 使用指定的配置参数初始化 CRNNRecognizer。
   * 识别器基于 CRNN (卷积循环神经网络) 架构，用于将文本区域图像
   * 转换为可读的文本字符串，支持中英文等多种语言。
   * 
   * @param model_dir 包含推理模型文件的目录路径
   *                  (inference.pdmodel, inference.pdiparams, inference.yml)
   * @param use_gpu 是否使用 GPU 进行推理 (true) 或使用 CPU (false)
   * @param gpu_id 要使用的 GPU 设备 ID (仅在 use_gpu=true 时有效)
   * @param gpu_mem GPU 内存限制，单位 MB (仅在 use_gpu=true 时有效)
   * @param cpu_math_library_num_threads 数学库使用的 CPU 线程数
   * @param use_mkldnn 是否启用 Intel MKL-DNN 优化进行 CPU 推理
   * @param label_path 字符字典文件路径，包含模型可识别的所有字符
   * @param use_tensorrt 是否启用 TensorRT 优化 (需要 TensorRT 和 GPU)
   * @param precision 推理精度 ("fp32", "fp16", "int8")
   * @param rec_batch_num 批处理大小，同时处理的文本区域图像数量
   * @param rec_img_h 输入图像的标准化高度 (像素)
   * @param rec_img_w 输入图像的标准化宽度 (像素)
   * 
   * @throws std::runtime_error 如果模型加载失败或字典文件读取失败
   * @throws YAML::Exception 如果 inference.yml 解析失败
   * @throws std::ios_base::failure 如果字符字典文件无法打开
   * 
   * @note 构造函数标记为 explicit 以防止隐式转换
   * @note 会自动在字符列表开头添加 CTC 空白字符 "#"，末尾添加空格字符
   * @note 如果 YAML 配置中包含字符字典，会自动生成新的字典文件
   * @note 构造函数是 noexcept，但在关键错误时可能调用 std::exit()
   */
  explicit CRNNRecognizer(const std::string &model_dir, const bool &use_gpu,
                          const int &gpu_id, const int &gpu_mem,
                          const int &cpu_math_library_num_threads,
                          const bool &use_mkldnn, const std::string &label_path,
                          const bool &use_tensorrt,
                          const std::string &precision,
                          const int &rec_batch_num, const int &rec_img_h,
                          const int &rec_img_w) noexcept {
    this->use_gpu_ = use_gpu;
    this->gpu_id_ = gpu_id;
    this->gpu_mem_ = gpu_mem;
    this->cpu_math_library_num_threads_ = cpu_math_library_num_threads;
    this->use_mkldnn_ = use_mkldnn;
    this->use_tensorrt_ = use_tensorrt;
    this->precision_ = precision;
    this->rec_batch_num_ = rec_batch_num;
    this->rec_img_h_ = rec_img_h;
    this->rec_img_w_ = rec_img_w;
    std::vector<int> rec_image_shape = {3, rec_img_h, rec_img_w};
    this->rec_image_shape_ = rec_image_shape;

    this->label_list_ = Utility::ReadDict(label_path);
    this->label_list_.emplace(this->label_list_.begin(), "#"); // blank char for ctc
    this->label_list_.emplace_back(" ");

    LoadModel(model_dir);
  }

  // Load Paddle inference model
  void LoadModel(const std::string &model_dir) noexcept;

  void Run(const std::vector<cv::Mat> &img_list,
           std::vector<std::string> &rec_texts,
           std::vector<float> &rec_text_scores,
           std::vector<double> &times) noexcept;

private:
  std::shared_ptr<paddle_infer::Predictor> predictor_;

  bool use_gpu_ = false;
  int gpu_id_ = 0;
  int gpu_mem_ = 4000;
  int cpu_math_library_num_threads_ = 4;
  bool use_mkldnn_ = false;

  std::vector<std::string> label_list_;

  std::vector<float> mean_ = {0.5f, 0.5f, 0.5f};
  std::vector<float> scale_ = {1 / 0.5f, 1 / 0.5f, 1 / 0.5f};
  bool is_scale_ = true;
  bool use_tensorrt_ = false;
  std::string precision_ = "fp32";
  int rec_batch_num_ = 6;
  int rec_img_h_ = 32;
  int rec_img_w_ = 320;
  std::vector<int> rec_image_shape_ = {3, rec_img_h_, rec_img_w_};
  // pre-process
  CrnnResizeImg resize_op_;
  Normalize normalize_op_;
  PermuteBatch permute_op_;

}; // class CrnnRecognizer

} // namespace PaddleOCR
